Intelligent evaluation method and system for postoperative rehabilitation progress

Abstract

The invention relates to the technical field of medical data, and discloses a postoperative rehabilitation progress intelligent evaluation method and system.According to the postoperative rehabilitation progress intelligent evaluation method and system, medical record data and postoperative rehabilitation data of all patients are obtained through a multi-dimensional management module and classified to form a patient data set and a progress data set; the intelligent evaluation module analyzes the operation difficulty of each patient in the treatment process and the postoperative rehabilitation state of the patient according to the patient data set and the progress data set, generates a corresponding difficulty coefficient and a corresponding reaction coefficient, quantifies the operation risk and the physiological response of the patient to the operation treatment scheme, pays attention to the individual difference, and improves the treatment efficiency. The intelligent evaluation module analyzes the change trend of postoperative rehabilitation data of each patient and generates a corresponding trend data set, the dynamic analysis precision is high, the health condition, the postoperative rehabilitation state and the postoperative rehabilitation progress of the patient are evaluated, corresponding rehabilitation suggestions are output, progress feedback is visualized, and the personalized rehabilitation management treatment effect is good.

Description

Technical Field

[0001] The present invention relates to the field of medical data technology, and in particular to a method and system for intelligently evaluating postoperative rehabilitation progress. Background Art

[0002] Postoperative rehabilitation refers to the process of helping patients restore physical function, reduce complications, and improve their quality of life through systematic intervention. Its core goal is to shorten the recovery period and ensure that patients can safely return to their daily lives or work. The principles of postoperative rehabilitation include early rehabilitation, individualization, and gradual progress. Rehabilitation treatment should be started as early as possible after surgery to prevent complications and promote healing. The rehabilitation plan must be tailored to the specific situation of each patient, including physical fitness, condition, psychological quality, etc. Rehabilitation training should gradually increase in intensity to avoid secondary injuries caused by excessive training. In addition to physiological indicators, functional tests and other methods are also needed to evaluate the progress of postoperative rehabilitation. By comparing physiological indicators, postoperative CT and other imaging examinations with those before surgery, observing the healing of the incision, and checking symptoms such as redness, swelling, exudation, and pain, the effect of the surgery can be intuitively reflected. Functional tests include evaluating joint range of motion, muscle strength, and walking ability, judging whether the distal joint activity of the fracture is limited, and whether basic movements such as hip lifting and sitting up can be completed, such as evaluating knee joint range of motion and walking ability after knee replacement. Slow or fast postoperative rehabilitation progress will have an adverse effect on the patient's recovery. Insufficient rehabilitation training may increase the chance of recurrence of disease or injury because the patient fails to gain sufficient physical strength and resistance through systematic training. Too fast a rehabilitation process may make the body unable to adapt to intense activities, leading to new injuries or worsening of unhealed wounds. Only by formulating a scientific rehabilitation plan based on individual conditions and conducting systematic rehabilitation training under the guidance of professional rehabilitation physicians and therapists can we ensure that the training time and intensity at each stage are appropriate to achieve the best rehabilitation effect.

[0003] At present, the traditional intelligent assessment method of postoperative rehabilitation progress relies on human power to judge the patient's recovery status, which is prone to misjudgment, missed diagnosis and other problems. When dealing with complex conditions, the data analysis capabilities are insufficient and the dynamic analysis accuracy is low. It is difficult to timely warn of postoperative complications, and the rehabilitation treatment effect is poor. Summary of the invention

[0004] 1. Technical issues to be resolved In view of the shortcomings of the existing technology, the present invention provides a method and system for intelligent assessment of postoperative rehabilitation progress, which has the advantages of high dynamic analysis accuracy and good personalized management and treatment effect. It solves the problem that the traditional intelligent assessment method for postoperative rehabilitation progress has low dynamic analysis accuracy and difficulty in timely warning of postoperative complications.

[0005] (II) Technical solution To achieve the above object, the present invention provides the following technical solution: a method for intelligently evaluating the progress of postoperative rehabilitation, comprising the following steps: Step 1: Connect to the hospital information management system through the network to obtain the medical records and postoperative rehabilitation data of all patients, and classify them into patient data sets and progress data sets; Step 2: Based on the patient data set, analyze the surgical difficulty of each patient during treatment and generate the corresponding difficulty coefficient ; Step 3: Analyze the postoperative recovery status of each patient based on the patient data set and progress data set, and generate the corresponding response coefficient ; Step 4: Set a fixed monitoring period , combined with the progress data set, analyze the change trend of each patient's postoperative rehabilitation data and generate the corresponding trend data set ; Step 5: Set a fixed range of difficulty thresholds and reaction threshold , combined with the difficulty coefficient , reaction coefficient and trend data groups , assess the patient’s health status, postoperative recovery status, and postoperative recovery progress, and output corresponding rehabilitation suggestions.

[0006] Preferably, in step 1, the expression of the patient data set is , to Indicates first to The medical records of patients include the patient's name, medical condition level, number of surgical steps, surgical anesthesia level, and preoperative physiological indicators. Represents the number of surgeries for a single patient.

[0007] Preferably, in step 1, the expression of the progress data set is , to Indicates first to The postoperative rehabilitation data of patients included postoperative physiological indicators, pain level, complication severity level, drug allergic reaction level and life ability score. Indicates the specific time point for obtaining the postoperative rehabilitation data of a single patient.

[0008] Preferably, in step 2, the difficulty coefficient The calculation process is as follows: According to the patient data set, extract the The medical records of the patients and The patient's condition level is marked as , will The number of surgical steps per patient is marked as , will The level of anesthesia for the surgery of the patients was marked as ; ; In the formula, represents the weight for the disease condition level, represents the weight for the number of surgical steps, represents the weight of the level of anesthesia for surgery, , and are constants, and , Indicates according to , and Weight, calculate the Difficulty of surgery for each patient .

[0009] Preferably, in step 3, the reaction coefficient The calculation process is as follows: According to the patient data set, The preoperative physiological indicators of the patients were marked as ; According to the progress data set, The postoperative physiological indicators of the patients were marked as , will The postoperative pain level of the patients was marked as , will The severity of postoperative complications in patients was marked as , will The grade of drug allergic reaction after surgery was marked as , will The postoperative life ability scores of the patients were marked as ; ; In the formula, It represents the difference between postoperative and preoperative physiological indicators. Indicates the standard value for measuring whether the difference in physiological indicators is abnormal. It represents the difference between postoperative and preoperative physiological indicators. Indicates the standard value for measuring whether the difference in physiological indicators is abnormal. Represents the weight of the ratio of the difference between the physiological index and the standard value, represents the weight for the pain level, represents the weight of the severity of complications, , , , and are constants, and , Indicates according to , , , and Weight, calculate the The postoperative response coefficient of patients .

[0010] Preferably, in step 4, the trend data group The calculation process is as follows: Extract monitoring cycles based on progress data set within, no. The postoperative recovery data of patients, among which, hour, , No. The physiological indexes of the patients after surgery were ,Will At that time, The postoperative pain level of the patients was marked as ,Will At that time, The severity of postoperative complications in patients was marked as ,Will At that time, The grade of drug allergic reaction after surgery was marked as ,Will At that time, The postoperative life ability scores of the patients were marked as ; ; In the formula, Indicated in At that time, Physiological indicators of patients after surgery, Indicated in At that time, Physiological indicators of patients after surgery, express to During the period, The changes of physiological indicators of patients after surgery, Indicated in At that time, The postoperative pain level of the patients Indicated in At that time, The postoperative pain level of the patients express to During the period, The change in pain level after surgery for each patient, Indicated in At that time, The severity of postoperative complications in patients Indicated in At that time, The severity of postoperative complications in patients express to During the period, The change in severity of postoperative complications among patients, Indicated in At that time, The degree of drug allergic reaction after surgery in patients Indicated in At that time, The degree of drug allergic reaction after surgery in patients express to During the period, The change in the level of drug allergic reaction after surgery in patients Indicated in At that time, The postoperative life ability scores of the patients were Indicated in At that time, The postoperative life ability scores of the patients were express to During the period, The change in the postoperative living ability score of the patients was Indicates monitoring cycle within, no. The change in the postoperative rehabilitation data of the patients is the trend data group.

[0011] Preferably, in step 5, the number of surgeries for a single patient is greater than 1 or the difficulty coefficient is greater than Exceeding Difficulty Threshold When the patient's health condition requires prolonged recovery, it is recommended that the patient stay in hospital for observation for a longer period of time.

[0012] Preferably, in step 5, the reaction coefficient Exceeding the reaction threshold It indicates that the patient's postoperative recovery is not good and it is recommended to adjust the rehabilitation treatment.

[0013] Preferably, in step 5, according to the trend data group Generate a corresponding trend line graph. If the trend line graph shows a downward trend over time, it means that the patient's postoperative recovery progress is too slow, and the patient is advised to reduce the amount of activity.

[0014] An intelligent assessment system for postoperative rehabilitation progress, comprising a multi-dimensional management module and an intelligent assessment module; The multi-dimensional management module is composed of a preoperative data unit and a postoperative data unit. The preoperative data unit is connected to the hospital information management system through a network to collect a patient data set, and the patient data set includes the medical history data of all patients. The postoperative data unit is connected to the hospital information management system through a network to collect a progress data set, and the progress data set includes the rehabilitation data of all patients after surgery. The intelligent assessment module consists of a preoperative assessment unit, a postoperative assessment unit and a rehabilitation management unit. The preoperative assessment unit analyzes the surgical difficulty of each patient during treatment based on the patient data set and generates a corresponding difficulty coefficient. The postoperative evaluation unit analyzes the postoperative recovery status of each patient according to the patient data set and the progress data set, and generates a corresponding reaction coefficient The postoperative assessment unit is provided with a monitoring cycle of fixed duration. , combined with the progress data set, analyze the change trend of each patient's postoperative rehabilitation data and generate the corresponding trend data set The rehabilitation management unit is set with a fixed range of difficulty thresholds and reaction threshold , combined with the difficulty coefficient , reaction coefficient and trend data groups , assess the patient’s health status, postoperative recovery status, and postoperative recovery progress, and output corresponding rehabilitation suggestions.

[0015] Compared with the prior art, the present invention provides a method and system for intelligent assessment of postoperative rehabilitation progress, which has the following beneficial effects: The present invention connects the hospital information management system through a multi-dimensional management module network to obtain the medical records and postoperative rehabilitation data of all patients, and classifies them into patient data sets and progress data sets, providing multi-dimensional and full-cycle data support for evaluation. The intelligent evaluation module analyzes the surgical difficulty of each patient's treatment process according to the patient data set and generates the corresponding difficulty coefficient , quantify surgical risks, assist medical staff in adjusting anesthesia plans or extending postoperative monitoring time, analyze each patient's postoperative recovery status, and generate corresponding response coefficients , quantify the patient's physiological response to surgical treatment options, focus on individual differences, and set a fixed-duration monitoring cycle for the intelligent assessment module , analyze the changing trend of each patient's postoperative rehabilitation data and generate the corresponding trend data set ,Dynamic tracking data can better reflect the true trajectory of rehabilitation, and dynamic analysis has high accuracy.

[0016] The present invention sets a fixed range of difficulty thresholds through an intelligent evaluation module and reaction threshold , combined with the difficulty coefficient , reaction coefficient and trend data groups , assess the patient's health status, postoperative recovery status, and postoperative recovery progress. The number of surgeries for a single patient is greater than 1 or the difficulty coefficient is Exceeding Difficulty Threshold When the patient's health condition requires a longer recovery time, it is recommended to extend the hospital observation time. Exceeding the reaction threshold When the patient is in poor recovery after surgery, it is recommended to adjust the rehabilitation treatment method. Threshold-driven graded intervention can quickly warn and reduce the cost of complications. Generate a corresponding trend line graph. If the trend line graph shows a downward trend over time, it means that the patient's postoperative rehabilitation progress is too slow. The patient is advised to reduce the amount of activity, visualize progress feedback, and achieve better personalized rehabilitation management and treatment results. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a step diagram of the method of the present invention; Figure 2 Schematic diagram of the system structure of the present invention. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0019] Since the traditional intelligent assessment method for postoperative rehabilitation progress relies on human judgment of the patient's rehabilitation status, it is prone to misjudgment and missed diagnosis. When dealing with complex conditions, the data analysis ability is insufficient, the dynamic analysis accuracy is low, and it is difficult to timely warn of postoperative complications. The rehabilitation treatment effect is poor. Therefore, a method and system for intelligent assessment of postoperative rehabilitation progress are provided. Please refer to Figure 1 , a postoperative rehabilitation progress intelligent assessment method, comprising the following steps: Step 1: Connect to the hospital information management system through the network to obtain the medical records and postoperative rehabilitation data of all patients, and classify them into patient data sets and progress data sets to provide multi-dimensional and full-cycle data support for the evaluation; The expression for the patient dataset is , to Indicates first to The medical records of patients include the patient's name, medical condition level, number of surgical steps, surgical anesthesia level, and preoperative physiological indicators. Indicates the number of surgeries for a single patient. Specifically, the condition level is assessed by the ASA grading system. From ASA-I to ASA-V, the higher the numerical value, the worse the patient's condition. Surgical anesthesia includes general anesthesia, local anesthesia, regional anesthesia and epidural anesthesia. The unified anesthesia levels are divided into 1, 2, 3 and 4. In the 1st level of anesthesia, the pain sensation, pain stimulation and vital signs of the operation are stable, and the patient is relatively comfortable after the operation. In the 2nd level of anesthesia, the hemodynamic changes of the patient during the operation fluctuate greatly, the muscle relaxation effect is not very good, and the patient feels uncomfortable after the operation. By analogy, the higher the numerical value, the worse the anesthesia tolerance. Preoperative physiological indicators are key indicators related to the patient's disease, such as glutathione S-transferase related to liver surgery; The expression of the progress data set is , to Indicates first to The postoperative rehabilitation data of patients included postoperative physiological indicators, pain level, complication severity level, drug allergic reaction level and life ability score. Indicates the specific time point for obtaining the postoperative rehabilitation data of a single patient. Specifically, the pain level is divided into 1, 2, 3, 4, 5, 6, 7, 8, 9 and 10. The higher the level, the stronger the pain reaction. The severity of complications is assessed by the Clavien-Dindo grading system. From level Ⅰ to level Ⅳ, the higher the numerical value, the more severe the patient's complications. The drug allergic reaction level is assessed by the immediate drug reaction grading scale. From level 0 to level 4, the higher the numerical value, the more severe the patient's drug allergic reaction. The life ability score is assessed by the PULSES rating scale. 6 points represent the best function, a score ≥12 points indicates that independent self-care life is severely limited, and a score ≥16 points indicates severe disability. Step 2: Based on the patient data set, analyze the surgical difficulty of each patient during treatment and generate the corresponding difficulty coefficient The calculation process is as follows: According to the patient data set, extract the The medical records of the patients and The patient's condition level is marked as , will The number of surgical steps per patient is marked as , will The level of anesthesia for the surgery of the patients was marked as ; ; In the formula, represents the weight for the disease condition level, represents the weight for the number of surgical steps, represents the weight of the level of anesthesia for surgery, , and are constants, and , Indicates according to , and Weight, calculate the Difficulty of surgery for each patient , quantify surgical risks and assist medical staff in adjusting anesthesia plans or extending postoperative monitoring time; Step 3: Analyze the postoperative recovery status of each patient based on the patient data set and progress data set, and generate the corresponding response coefficient The calculation process is as follows: According to the patient data set, The preoperative physiological indicators of the patients were marked as ; According to the progress data set, The postoperative physiological indicators of the patients were marked as , will The postoperative pain level of the patients was marked as , will The severity of postoperative complications in patients was marked as , will The grade of drug allergic reaction after surgery was marked as , will The postoperative life ability scores of the patients were marked as ; ; In the formula, It represents the difference between postoperative and preoperative physiological indicators. Indicates the standard value for measuring whether the difference in physiological indicators is abnormal. It represents the difference between postoperative and preoperative physiological indicators. Indicates the standard value for measuring whether the difference in physiological indicators is abnormal. Represents the weight of the ratio of the difference between the physiological index and the standard value, represents the weight for the pain level, represents the weight of the severity of complications, , , , and are constants, and , Indicates according to , , , and Weight, calculate the The postoperative response coefficient of patients , comprehensively consider the patient's individual constitution, condition, psychological quality and other factors, quantify the patient's physiological response to the surgical treatment plan, and pay attention to individual differences; Step 4: Set a fixed monitoring period , combined with the progress data set, analyze the change trend of each patient's postoperative rehabilitation data and generate the corresponding trend data set The calculation process is as follows: Extract monitoring cycles based on progress data set within, no. The postoperative recovery data of patients, among which, hour, , No. The physiological indexes of the patients after surgery were ,Will At that time, The postoperative pain level of the patients was marked as ,Will At that time, The severity of postoperative complications in patients was marked as ,Will At that time, The grade of drug allergic reaction after surgery was marked as ,Will At that time, The postoperative life ability scores of the patients were marked as ; ; In the formula, Indicated in At that time, Physiological indicators of patients after surgery, Indicated in At that time, Physiological indicators of patients after surgery, express to During the period, The changes of physiological indicators of patients after surgery, Indicated in At that time, The postoperative pain level of the patients Indicated in At that time, The postoperative pain level of the patients express to During the period, The change in pain level after surgery for each patient, Indicated in At that time, The severity of postoperative complications in patients Indicated in At that time, The severity of postoperative complications in patients express to During the period, The change in severity of postoperative complications among patients, Indicated in At that time, The degree of drug allergic reaction after surgery in patients Indicated in At that time, The degree of drug allergic reaction after surgery in patients express to During the period, The change in the level of drug allergic reaction after surgery in patients Indicated in At that time, The postoperative life ability scores of the patients were Indicated in At that time, The postoperative life ability scores of the patients were express to During the period, The change in the postoperative living ability score of the patients was Indicates monitoring cycle within, no. The change in the postoperative rehabilitation data of each patient is the trend data group, which helps to quickly identify abnormal fluctuations and trigger reexamination reminders; Step 5: Set a fixed range of difficulty thresholds and reaction threshold , combined with the difficulty coefficient , reaction coefficient and trend data groups , assess the patient's health status, postoperative rehabilitation status, and postoperative rehabilitation progress, and output corresponding rehabilitation suggestions; The number of surgeries for a single patient is greater than 1 or the difficulty coefficient Exceeding Difficulty Threshold When the patient's health condition requires a longer recovery time, it is recommended to extend the hospital observation time. Exceeding the reaction threshold When the patient is in poor recovery after surgery, it is recommended to adjust the rehabilitation treatment method. Threshold-driven graded intervention can quickly warn and reduce the cost of complications. Generate a corresponding trend line graph. If the trend line graph shows a downward trend over time, it means that the patient's postoperative rehabilitation progress is too slow. It is recommended that the patient reduce the amount of activity, visualize the progress feedback, and achieve better rehabilitation treatment results.

[0020] See also Figure 2 , an intelligent assessment system for postoperative rehabilitation progress, including a multi-dimensional management module and an intelligent assessment module; The multi-dimensional management module consists of a preoperative data unit and a postoperative data unit. The preoperative data unit is connected to the hospital information management system through the network to collect patient data sets, which include the medical records of all patients. The postoperative data unit is connected to the hospital information management system through the network to collect progress data sets, which include the postoperative rehabilitation data of all patients. The intelligent assessment module consists of a preoperative assessment unit, a postoperative assessment unit and a rehabilitation management unit. The preoperative assessment unit analyzes the surgical difficulty of each patient's treatment process based on the patient data set and generates a corresponding difficulty coefficient. The postoperative evaluation unit analyzes the postoperative recovery status of each patient based on the patient data set and progress data set, and generates the corresponding response coefficient , accurately identify individual differences among patients, and the postoperative evaluation unit has a fixed monitoring period , combined with the progress data set, analyze the change trend of each patient's postoperative rehabilitation data and generate the corresponding trend data set Dynamic tracking data can better reflect the real trajectory of rehabilitation, dynamic analysis is highly accurate, and the rehabilitation management unit is set with a fixed range of difficulty thresholds. and reaction threshold , combined with the difficulty coefficient , reaction coefficient and trend data groups , evaluate the patient's health status, postoperative rehabilitation status, and postoperative rehabilitation progress, and output corresponding rehabilitation suggestions. Personalized rehabilitation management has good treatment effects.

[0021] Example 1: In this example, a patient who needs to undergo thyroid nodule surgery is selected as the experimental subject. After testing, the patient's condition level is level 3, the number of surgical steps is 5, the surgical anesthesia level is level 2, and the patient's difficulty coefficient is The calculation process is as follows: ; ; In the formula, the weight for the disease condition level is 0.5, the weight for the number of surgical steps is 0.3, and the weight for the level of surgical anesthesia is 0.2. , and are constants, and ,according to , and Weight, calculate the difficulty coefficient of the patient's surgery is 3.4.

[0022] Example 2: In this example, a patient who needs to undergo renal artery stent implantation surgery is selected as the experimental subject. After testing, the patient's preoperative diastolic blood pressure is 95 mmHg, the postoperative diastolic blood pressure is 65 mmHg, the postoperative pain level is level 3, the postoperative complication severity level is level 2, the postoperative drug allergic reaction level is level 1, the postoperative life ability score is 4, and the patient's reaction coefficient is The calculation process is as follows: ; ; In the formula, It represents the difference between postoperative physiological indicators and preoperative physiological indicators. The standard value for measuring whether the difference of physiological indicators is abnormal is -10. The weight for the ratio of the difference of physiological indicators to the standard value is 0.4, the weight for the pain level is 0.2, the weight for the severity of complications is 0.1, the weight for the drug allergic reaction level is 0.15, and the weight for the living ability score is 0.15. , , , and are constants, and ,according to , , , and Weight, calculate the patient's postoperative response coefficient is 2.75.

[0023] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for intelligent assessment of postoperative rehabilitation progress, characterized in that: The following steps are involved: Step 1: Connect to the hospital information management system through the network to obtain the medical records and postoperative rehabilitation data of all patients, and classify them into patient data sets and progress data sets; Step 2: Based on the patient data set, analyze the surgical difficulty of each patient during treatment and generate the corresponding difficulty coefficient ; Step 3: Analyze the postoperative recovery status of each patient based on the patient data set and progress data set, and generate the corresponding response coefficient ; Step 4: Set a fixed monitoring period , combined with the progress data set, analyze the change trend of each patient's postoperative rehabilitation data and generate the corresponding trend data set ; Step 5: Set a fixed range of difficulty thresholds and reaction threshold , combined with the difficulty coefficient , reaction coefficient and trend data groups , assess the patient’s health status, postoperative recovery status, and postoperative recovery progress, and output corresponding rehabilitation suggestions.

2. The method for intelligent assessment of postoperative rehabilitation progress according to claim 1, characterized in that: In step 1, the expression of the patient data set is: , to Indicates first to The medical records of patients include the patient's name, medical condition level, number of surgical steps, surgical anesthesia level, and preoperative physiological indicators. Represents the number of surgeries for a single patient.

3. The intelligent assessment method for postoperative rehabilitation progress according to claim 2, characterized in that: In step 1, the expression of the progress data set is: , to Indicates first to The postoperative rehabilitation data of patients included postoperative physiological indicators, pain level, complication severity level, drug allergic reaction level and life ability score. Indicates the specific time point for obtaining the postoperative rehabilitation data of a single patient.

4. The intelligent assessment method for postoperative rehabilitation progress according to claim 3, characterized in that: In step 2, the difficulty coefficient The calculation process is as follows: According to the patient data set, extract the The medical records of the patients and The patient's condition level is marked as , will The number of surgical steps per patient is marked as , will The surgical anesthesia level of the patients was marked as ; set up , and weight, and , in which, represents the weight for the disease condition level, represents the weight for the number of surgical steps, Represents the weight of the surgical anesthesia level, according to , and Weight, calculate the Difficulty of surgery for each patient .

5. The intelligent assessment method for postoperative rehabilitation progress according to claim 4, characterized in that: In step 3, the reaction coefficient The calculation process is as follows: According to the patient data set, The preoperative physiological indicators of the patients were marked as ; According to the progress data set, The postoperative physiological indicators of the patients were marked as , will The postoperative pain level of the patients was marked as , will The severity of postoperative complications in patients was marked as , will The grade of drug allergic reaction after surgery was marked as , will The postoperative life ability scores of the patients were marked as ; set up , , , and weight, and , It represents the difference between postoperative and preoperative physiological indicators. Indicates the standard value for measuring whether the difference in physiological indicators is abnormal. Represents the weight of the ratio of the difference between the physiological index and the standard value, represents the weight for the pain level, Indicates the weight of the severity of complications, according to , , , and Weight, calculate the The postoperative response coefficient of patients .

6. The method for intelligent assessment of postoperative rehabilitation progress according to claim 5, characterized in that: In step 4, the trend data group The calculation process is as follows: Extract monitoring cycles based on progress data set within, no. The postoperative recovery data of patients, among which, hour, , No. The physiological indexes of the patients after surgery were ,Will At that time, The postoperative pain level of the patients was marked as ,Will At that time, The severity of postoperative complications in patients was marked as ,Will At that time, The grade of drug allergic reaction after surgery was marked as ,Will At that time, The postoperative life ability scores of the patients were marked as ; Will At the next time point, The postoperative rehabilitation data of the patients were marked in the same way; calculate to During the next time point, The changes in physiological indicators, pain level, complication severity level, drug allergic reaction level and life ability score of the patients after surgery were Indicates monitoring cycle within, no. The change in the postoperative rehabilitation data of the patients is the trend data group.

7. The intelligent assessment method for postoperative rehabilitation progress according to claim 6, characterized in that: Step 5: The number of surgeries for a single patient is greater than 1 or the difficulty coefficient Exceeding Difficulty Threshold When the patient's health condition requires a longer recovery time, it is recommended to extend the hospital observation time. Exceeding the reaction threshold When the patient's postoperative recovery is not good, it is recommended to adjust the rehabilitation treatment method. Generate a corresponding trend line graph. If the trend line graph shows a downward trend over time, it means that the patient's postoperative recovery progress is too slow, and the patient is advised to reduce the amount of activity.

8. A postoperative rehabilitation progress intelligent assessment system, applied to a postoperative rehabilitation progress intelligent assessment method according to any one of claims 1 to 7, characterized in that: Including multi-dimensional management module and intelligent evaluation module; The multi-dimensional management module is composed of a preoperative data unit and a postoperative data unit. The preoperative data unit is connected to the hospital information management system through a network to collect a patient data set, and the patient data set includes the medical history data of all patients. The postoperative data unit is connected to the hospital information management system through a network to collect a progress data set, and the progress data set includes the rehabilitation data of all patients after surgery. The intelligent assessment module consists of a preoperative assessment unit, a postoperative assessment unit and a rehabilitation management unit. The preoperative assessment unit analyzes the surgical difficulty of each patient during treatment based on the patient data set and generates a corresponding difficulty coefficient. The postoperative evaluation unit analyzes the postoperative recovery status of each patient according to the patient data set and the progress data set, and generates a corresponding reaction coefficient The postoperative assessment unit is provided with a monitoring cycle of fixed duration. , combined with the progress data set, analyze the change trend of each patient's postoperative rehabilitation data and generate the corresponding trend data set The rehabilitation management unit is set with a fixed range of difficulty thresholds and reaction threshold , combined with the difficulty coefficient , reaction coefficient and trend data groups , assess the patient’s health status, postoperative recovery status, and postoperative recovery progress, and output corresponding rehabilitation suggestions.

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